Machine Learning Methods in Visualisation for Big Data 2020

@inproceedings {N20037:2020,
booktitle = {Machine Learning Methods in Visualisation for Big Data},
editor = {Archambault, Daniel and Nabney, Ian and Peltonen, Jaakko},
title = {{Progressive Multidimensional Projections: A Process Model based on Vector Quantization}},
author = {Ventocilla, Elio Alejandro and Martins, Rafael M. and Paulovich, Fernando V. and Riveiro, Maria},
year = {2020},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-113-7},
pages = {1-5},
DOI = {10.2312/mlvis.20201099}
}
@inproceedings {N200C9:2020,
booktitle = {Machine Learning Methods in Visualisation for Big Data},
editor = {Archambault, Daniel and Nabney, Ian and Peltonen, Jaakko},
title = {{ModelSpeX: Model Specification Using Explainable Artificial Intelligence Methods}},
author = {Schlegel, Udo and Cakmak, Eren and Keim, Daniel A.},
year = {2020},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-113-7},
pages = {7-11},
DOI = {10.2312/mlvis.20201100}
}
@inproceedings {N2006B:2020,
booktitle = {Machine Learning Methods in Visualisation for Big Data},
editor = {Archambault, Daniel and Nabney, Ian and Peltonen, Jaakko},
title = {{Visual Analysis of the Impact of Neural Network Hyper-Parameters}},
author = {Jönsson, Daniel and Eilertsen, Gabriel and Shi, Hezi and Zheng, Jianmin and Ynnerman, Anders and Unger, Jonas},
year = {2020},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-113-7},
pages = {13-17},
DOI = {10.2312/mlvis.20201101}
}
@inproceedings {N20009:2020,
booktitle = {Machine Learning Methods in Visualisation for Big Data},
editor = {Archambault, Daniel and Nabney, Ian and Peltonen, Jaakko},
title = {{Improving the Sensitivity of Statistical Testing for Clusterability with Mirrored-Density Plots}},
author = {Thrun, Michael C.},
year = {2020},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-113-7},
pages = {19-23},
DOI = {10.2312/mlvis.20201102}
}
@inproceedings {N200FB:2020,
booktitle = {Machine Learning Methods in Visualisation for Big Data},
editor = {Archambault, Daniel and Nabney, Ian and Peltonen, Jaakko},
title = {{Visual Interpretation of DNN-based Acoustic Models using Deep Autoencoders}},
author = {Grósz, Tamás and Kurimo, Mikko},
year = {2020},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-113-7},
pages = {25-29},
DOI = {10.2312/mlvis.20201103}
}